Max obtained his bachelor’s degree in physics and in computer science from the University of Minnesota, Twin Cities in 2014, and continued to a master’s and finally a PhD at the University of Cambridge in 2018. His PhD work with Gábor Csányi focused on developing machine learning (ML) models for accurate atomistic simulation of molecular liquids. Before joining Miguel Caro’s group at Aalto University in 2022, he was a postdoc in the COSMO group at EPFL, led by Michele Ceriotti, where he worked on improving the efficiency and expanding the capability of atomistic ML simulations, for instance by including tensorial ML models that allow dielectric properties to be computed from first principles. Now, in Miguel Caro’s group, he is working to apply such physics-inspired ML models to practical problems that push the frontiers of chemical complexity, system size, and predictive capability currently achievable with ML atomistic simulations.